Question 3 Using the below data, what is the regression equation? Coefficients Standard Error t-Stat p-value Intercept -12.201 6.560 -1.860 0.100 Number of Contacts 2.195 0.176 12.505 0.000 O Y = 2.195 - 12.201X O Y = -12.201 + 2.195X O Y = 12.201 + 2.195X O Y = 2.195 + 12.201XQuestion 4 Using the below data, what is the coefficient of determination? Coefficients Intercept -12.8094 Independent Variable 2.1794 ANOVA SS MS F Regression 100 9 12323.56 12323.50 90.0481 Residual 1094.842 136.8552 Total 9 13418.4 O 0.9184 0 0.9583 O -0.9583 0 0.9004A multiple regression analysis showed the following results of the individual independent variables. X4 is a qualitative variable (i.e., it takes on the value 0 or 1). If X4 is equal to one, what is the variable's effect on the dependent variable? Standard Coefficients Error t-stat p-value Intercept 139.577 84.235 1.657 -0.135 5.698 -0.024 3.734 1.220 3.062 2.448 26.524 0.376 9.976 1.044 2.345 O The dependent variable will decrease by 9.976 units. 0 The dependent variable will increase by 9.976 units. 0 The dependent variable will not be affected because the coefcient on X4 cannot be said to be statistically different than zero. 0 The dependent variable will increase by 2*9.976 units. General Instructions: A. This practice problem set is intended to familiarize the student with the practice of multiple regression. B. Please follow the directions below and use Excel to make calculations. The data contains crime rates and factors that might inuence crime rates. Please review data set for variable names and denitions. Models Model 1: Rate = Age Model 2: Rate = Age Education Expend_60 U2 INEQUAL South LFPR MALE_F TOT_POP NW_POP U1 Income Expend_59 Model 3: Rate = Age Education Expend_60 U2 INEQUAL South LFPR MALE_F TOT_POP NW_POP U1 Income (Same as Model 2 but drop Expend_59) Model 4: Rate = Age Education Expend_60 U2 INEQUAL South LFPR MALE_F TOT_POP NW_POP U1 (Same as Model 3 but drop Income) 1. Estimate Mode14 using Excel's regression function. Choose to output residuals, standardized residuals, and the normal probability plot from the Regression options section. (It will be easier if you choose \"New Worksheet Ply\" for the output. Excel will create a new tab and place the output in that tab.) a. What happened to the adjusted R-Square relative to Model 3 (either use last week's output or re-run Model 3)? \fa.Which variables are signicant at the 5% level b. What does the Ftest tell us? c. 'What are the estimates of Expend759 and Exp d. Do the signs make sense? (you need not find the cut off t-value, use the p-value to answer this question)? end 60?Table 2: Correlation Coefficient Matrix Rate Age Education Expend 60 U2 Rate 1.0000 -0.0895 0.3228 0.6876 0.1773 Age 1.0000 -0.5302 -0.5057 -0.2448 Education 1.0000 0.4830 -0.2157 Expend 60 1.0000 0.1851 U2 1.0000 INEQUAL South LFPR MALE F TOT POP NW POP U1 INCOME Expend 59Name Rate Age South Education Expend_60 Expend 59 LFPR MALE F TOT POP NW POP U 1 U 2 INCOME INEQUAL